Ultrasonic characterization of non-linear properties of tissue

ABSTRACT

Systems and methods for performing diagnostic sonography. Ultrasound information of a subject region can be collected. The ultrasound information can be based on one or more exponentially swept ultrasound chirp pulses transmitted toward the subject region and backscatter of the subject region from the one or more exponentially swept ultrasound chirp pulses. One or more corresponding harmonic responses and a corresponding fundamental response for each of the one or more exponentially swept ultrasound chirp pulses can be separated from the ultrasound information. Further, one or more non-linear properties of the subject region can be identified based on either or both of the one or more corresponding harmonic responses and the corresponding fundamental response for each of the one or more exponentially swept ultrasound chirp pulses.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/832,388 to Glen W. McLaughlin et al., titled ULTRASONIC TISSUECHARACTERIZATION OF THE B/A COEFFICIENT, and filed Apr. 11, 2019, theentire disclosure of which is hereby incorporated herein by thisreference.

TECHNICAL FIELD

The present disclosure relates to diagnostic sonography and moreparticularly to identifying non-linear properties of tissue throughexponentially swept ultrasound chirp pulses.

BACKGROUND OF THE INVENTION

Ultrasound imaging is widely used for examining a wide range ofmaterials and objects across a wide array of different applications.Ultrasound imaging provides a fast and easy tool for analyzing materialsand objects in a non-invasive manner. As a result, ultrasound imaging isespecially common in the practice of medicine as an ailment diagnosis,treatment, and prevention tool. Specifically, because of its relativelynon-invasive nature, low cost and fast response time ultrasound imagingis widely used throughout the medical industry to diagnose and preventailments. Further, as ultrasound imaging is based on non-ionizingradiation it does not carry the same risks as other diagnosis imagingtools, such as X-ray imaging or other types of imaging systems that useionizing radiation.

Characterization of tissue properties, and in particular in-vivo tissueproperties, with ultrasound has been a long-standing area of researchfor the past several decades. Specifically, efforts have been undertakento efficiently gather and interpret ultrasound measurements forcharacterizing both bulk tissue properties and regional tissueproperties. However, extracting meaningful and consistent ultrasoundmeasurements and interpreting these ultrasound measurements to identifytissue properties has been challenging endeavor for numerous reasons.

SUMMARY

According to various embodiments, a method for performing diagnosticsonography includes collecting ultrasound information of a subjectregion. The ultrasound information can be based on one or moreexponentially swept ultrasound chirp pulses transmitted toward thesubject region and backscatter of the subject region from the one ormore exponentially swept ultrasound chirp pulses. The method can alsoinclude separating one or more corresponding harmonic responses and acorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses from the ultrasoundinformation. Further, the method can include identifying one or morenon-linear properties of the subject region based on either or both ofthe one or more corresponding harmonic responses and the correspondingfundamental response for each of the one or more exponentially sweptultrasound chirp pulses.

In certain embodiments, a system for performing diagnostic sonographyincludes an ultrasound transducer and a main processing console. Theultrasound transducer can collect ultrasound information of a subjectregion. The ultrasound information can be based on one or moreexponentially swept ultrasound chirp pulses transmitted toward thesubject region and backscatter of the subject region from the one ormore exponentially swept ultrasound chirp pulses. The main processingconsole can separate one or more corresponding harmonic responses and acorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses from the ultrasoundinformation. The main processing console can also identify one or morenon-linear properties of the subject region based on either or both ofthe one or more corresponding harmonic responses and the correspondingfundamental response for each of the one or more exponentially sweptultrasound chirp pulses.

In various embodiments, a system for performing diagnostic sonographyincludes one or more processors and a computer-readable medium providinginstructions accessible to the one or more processors to cause the oneor more processors to collect ultrasound information of a subjectregion. The ultrasound information can be based on one or moreexponentially swept ultrasound chirp pulses transmitted toward thesubject region and backscatter of the subject region from the one ormore exponentially swept ultrasound chirp pulses. The instructions canfurther cause the one or more processors to separate one or morecorresponding harmonic responses and a corresponding fundamentalresponse for each of the one or more exponentially swept ultrasoundchirp pulses from the ultrasound information. Additionally, theinstructions can cause the one or more processors to identify one ormore non-linear properties of the subject region based on either or bothof the one or more corresponding harmonic responses and thecorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of an ultrasound system.

FIG. 2 is a plot of intensities of fundamental and harmonic responses toan exponentially swept ultrasound chirp pulse as a function of time forboth linear and non-linear subject regions.

FIG. 3A is a positive phase image of a subject region created through aGaussian ultrasound transmit profile.

FIG. 3B is a negative phase image of the subject region created throughthe Gaussian ultrasound transmit profile.

FIG. 3C is a sum image of the images shown in FIGS. 3A and 3B.

FIG. 3D is a difference image of the images shown in FIGS. 3A and 3B.

FIG. 4A is an intensity plot of fundamental and harmonic responses to anarrowband Gaussian transmit profile centered at a 10 mm depth.

FIG. 4B is an intensity plot of the fundamental and harmonic responsesto the narrowband Gaussian transmit profile centered at a 20 mm depth.

FIG. 4C is an intensity plot of the fundamental and harmonic responsesto the narrowband Gaussian transmit profile centered at a 30 mm depth.

FIG. 4D is an intensity plot of the fundamental and harmonic responsesto the narrowband Gaussian transmit profile centered at a 40 mm depth.

FIG. 4E is an intensity plot of the fundamental and harmonic responsesto the narrowband Gaussian transmit profile centered at a 50 mm depth.

FIG. 4F is an intensity plot of the fundamental and harmonic responsesto the narrowband Gaussian transmit profile centered at a 60 mm depth.

FIG. 5A is a positive phase image of a subject region created through anexponentially swept ultrasound chirp signal.

FIG. 5B is a negative phase image of the subject region created throughthe exponentially swept ultrasound chirp signal.

FIG. 5C is a sum image of the images shown in FIGS. 5A and 5B.

FIG. 5D is a difference image of the images shown in FIGS. 5A and 5B.

FIG. 6A is an intensity plot of fundamental and harmonic responses to anexponentially swept ultrasound chirp pulse centered at a 10 mm depth.

FIG. 6B is an intensity plot of the fundamental and harmonic responsesto the exponentially swept ultrasound chirp pulse centered at a 20 mmdepth.

FIG. 6C is an intensity plot of the fundamental and harmonic responsesto the exponentially swept ultrasound chirp pulse centered at a 30 mmdepth.

FIG. 6D is an intensity plot of the fundamental and harmonic responsesto the exponentially swept ultrasound chirp pulse centered at a 40 mmdepth.

FIG. 6E is an intensity plot of the fundamental and harmonic responsesto the exponentially swept ultrasound chirp pulse centered at a 50 mmdepth.

FIG. 6F is an intensity plot of the fundamental and harmonic responsesto the exponentially swept ultrasound chirp pulse centered at a 60 mmdepth.

FIG. 7A is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6A centered at a 10 mm depth.

FIG. 7B is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6B centered at a 20 mm depth.

FIG. 7C is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6C centered at a 30 mm depth.

FIG. 7D is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6D centered at a 40 mm depth.

FIG. 7E is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6E centered at a 50 mm depth.

FIG. 7F is a plot of sums and differences of the fundamental andharmonic responses in FIG. 6F centered at a 60 mm depth.

FIG. 8 is a flowchart of an example method for identifying non-linearproperties of a subject region through an exponentially swept ultrasoundchirp pulse.

FIG. 9 is a flowchart of an example method for estimating a B/Aparameter of a subject region through an exponential swept ultrasoundchirp signal.

DETAILED DESCRIPTION

Characterization of tissue properties, and in particular in-vivo tissueproperties, with ultrasound has been a long-standing area of researchfor the past several decades. Specifically, efforts have been undertakento efficiently gather and interpret ultrasound measurements forcharacterizing both bulk tissue properties and regional tissueproperties. However, extracting meaningful and consistent ultrasoundmeasurements and interpreting these ultrasound measurements to identifytissue properties has been challenging endeavor for numerous reasons.First, basic ultrasound measurements tend to be operator dependentmaking it difficult to consistently and accurately identify tissuecharacteristics from measurements gathered across different operators.Additionally, ultrasound measurements are prone to noise making itdifficult to accurately identify tissue characteristics from themeasurements. Further, ultrasound can have difficulties penetratingareas of interest at great depths making it difficult to gathermeasurements for accurately identifying tissue characteristics of theareas of interest. Additionally, correlation across different ultrasoundsystem implementations is challenging, thereby leading to consistencyand accuracy issues associated with characterizing tissue frommeasurements gathered across the different system implementations.

With respect to in-vivo tissue properties, movement of the tissuecreates problems in gathering meaningful ultrasound measurements andaccurately identifying tissue characteristics from the measurements. Asa result, measurements for identifying tissue characteristics, e.g.non-linear tissue characteristics, are typically made through excisedtissue. However, the process of surgically removing a patient's tissuecomplicates the overall process of tissue characterization and presentsnumerous risks for the patient.

The following disclosure describes systems, methods, andcomputer-readable media for solving these problems/discrepancies.Specifically, the present technology involves system, methods, andcomputer-readable media for identifying non-linear properties of asubject region through one or more exponentially swept ultrasound chirppulses transmitted towards the subject region. More specifically, thepresent technology involves systems, methods, and computer-readablemedia for identifying non-linear properties of the subject region basedon either or both one or more corresponding harmonic responses and acorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses

Reference is now made to the figures, where like components aredesignated by like reference numerals throughout the disclosure. Some ofthe infrastructure that can be used with embodiments disclosed herein isalready available, such as general-purpose computers, computerprogramming tools and techniques, digital storage media, andcommunications networks. A computing device may include a processor suchas a microprocessor, microcontroller, logic circuitry, or the like. Theprocessor may include a special purpose processing device such as anASIC, PAL, PLA, PLD, FPGA, or other customized or programmable device.The computing device may also include a computer-readable storage devicesuch as non-volatile memory, static RAM, dynamic RAM, ROM, CD-ROM, disk,tape, magnetic, optical, flash memory, or other non-transitorycomputer-readable storage medium.

Various aspects of certain embodiments may be implemented usinghardware, software, firmware, or a combination thereof. As used herein,a software module or component may include any type of computerinstruction or computer executable code located within or on acomputer-readable storage medium. A software module may, for instance,comprise one or more physical or logical blocks of computerinstructions, which may be organized as a routine, program, object,component, data structure, etc., which performs one or more tasks orimplements particular abstract data types.

In certain embodiments, a particular software module may comprisedisparate instructions stored in different locations of acomputer-readable storage medium, which together implement the describedfunctionality of the module. Indeed, a module may comprise a singleinstruction or many instructions, and may be distributed over severaldifferent code segments, among different programs, and across severalcomputer-readable storage media. Some embodiments may be practiced in adistributed computing environment where tasks are performed by a remoteprocessing device linked through a communications network.

The embodiments of the disclosure will be best understood by referenceto the drawings. The components of the disclosed embodiments, asgenerally described and illustrated in the figures herein, could bearranged and designed in a wide variety of different configurations.Furthermore, the features, structures, and operations associated withone embodiment may be applicable to or combined with the features,structures, or operations described in conjunction with anotherembodiment. In other instances, well-known structures, materials, oroperations are not shown or described in detail to avoid obscuringaspects of this disclosure.

Thus, the following detailed description of the embodiments of thesystems and methods of the disclosure is not intended to limit the scopeof the disclosure, as claimed, but is merely representative of possibleembodiments. In addition, the steps of a method do not necessarily needto be executed in any specific order, or even sequentially, nor need thesteps be executed only once.

FIG. 1 is a schematic block diagram of one exemplary embodiment of amedical imaging device, such as an ultrasound imaging device 100. Thoseskilled in the art will recognize that the principles disclosed hereinmay be applied to a variety of medical imaging devices, including,without limitation, an X-ray imaging device, a computed tomography (CT)imaging device, a magnetic resonance imaging (MRI) device, and apositron-emission tomography (PET) imaging device. As such, thecomponents of each device may vary from what is illustrated in FIG. 1 .

In one embodiment, the ultrasound imaging device 100 may include anarray focusing unit, referred to herein as a beam former 102, by whichimage formation can be performed on a scanline-by-scanline basis. Thedevice may be controlled by a master controller 104, implemented by amicroprocessor or the like, which accepts operator inputs through anoperator interface and in turn controls the various subsystems of thedevice 100.

For each scanline, a transmitter 106 generates a radio-frequency (RF)excitation voltage pulse waveform and applies it with appropriate timingacross a transmit aperture (defined, in one embodiment, by a sub-arrayof active elements) to generate a focused acoustic beam along thescanline.

RF echoes received by one or more receive apertures or receiver 108 areamplified, filtered, and then fed into the beam former 102, which mayperform dynamic receive focusing, i.e., realignment of the RF signalsthat originate from the same locations along various scan lines.Collectively, the transmitter 106 and receiver 108 may be components ofa transducer 110. Various types of transducers 110 are known in theultrasound imaging art, such as linear probes, curvilinear probes, andphased array probes.

An image processor 112 may perform processing tasks specific to variousactive imaging mode(s) including 2D scan conversion that transforms theimage data from an acoustic line grid into an X-Y pixel image fordisplay. For other modes, such as a spectral Doppler mode, the imageprocessor 112 may perform wall filtering followed by spectral analysisof Doppler-shifted signal samples using typically a sliding FFT-window.The image processor 112 may also generate a stereo audio signal outputcorresponding to forward and reverse flow signals. In cooperation withthe master controller 104, the image processor 112 may also formatimages from two or more active imaging modes, including displayannotation, graphics overlays and replay of cine loops and recordedtimeline data.

A cine memory 114 provides resident digital image storage to enablesingle image or multiple image loop review, and acts as a buffer fortransfer of images to digital archival devices, such as hard disk drivesor optical storage. In some systems, the video images at the end of thedata processing path may be stored to the cine memory. Instate-of-the-art systems, amplitude-detected, beamformed data may alsobe stored in cine memory 114. For spectral Doppler mode, wall-filtered,baseband Doppler 1/Q data for a user-selected range gate may be storedin cine memory 114. Subsequently, a display 116, such as a computermonitor, may display ultrasound images created by the image processor112 and/or images using data stored in the cine memory 114.

The beam former 102, the master controller 104, the image processor 112,the cine memory 114, and the display 116 can be included as part of amain processing console 118 of the ultrasound imaging device 100, whichmay include more or fewer components or subsystems than are illustrated.The ultrasound transducer 110 may be incorporated into an apparatus thatis separate from the main processing console 118, e.g. in a separateapparatus that is wired or wirelessly connected to the main processingconsole 118. This allows for easier manipulation of the ultrasoundtransducer 110 when performing specific ultrasound procedures on apatient. Further, the transducer 110 can be an array transducer thatincludes an array of transmitting and receiving elements fortransmitting and receiving ultrasound waves.

Those skilled in the art will recognize that a wide variety ofultrasound imaging devices are available on the market, and additionaldetails relating to how images are generated is unnecessary for athorough understanding of the principles disclosed herein. Specifically,the systems, methods, and computer-readable media described herein canbe applied through an applicable ultrasound imaging device of the widevariety of ultrasound imaging devices available on the market.

Exponentially swept ultrasound chirps can be applied to characterizenon-linearity of a subject region. Specifically, exponentially sweptultrasound chirps can be applied to identify non-linear properties oftissue. More specifically, exponentially swept ultrasound chirps can beapplied to identify non-linear properties of in-vivo tissue.Characterizing tissue that remains in-vivo is advantageous as it reducesthe complexity associated with surgically removing the tissue toultimately characterize the tissue. Further, characterizing tissue thatremains in-vivo is advantageous as it eliminates patient risksassociated with the surgical procedure(s) of removing the tissue.

Non-linear properties of a subject region can include applicablenon-linear properties of a subject region capable of being identifiedthrough ultrasound. Specifically, non-linear properties of a subjectregion can include applicable acoustic non-linear properties of tissuecapable of being identified through ultrasound. For example, non-linearproperties of a subject region can include values of an acousticnon-linearity parameter B/A for tissue.

Exponentially swept chirp pulses can be represented as Equations 1 and 2shown below.

$\begin{matrix}{{x(t)} = e^{i2\pi\frac{f_{1}}{a}{({e^{at} - 1})}}} & {{Equation}1}\end{matrix}$ $\begin{matrix}{{\theta(f)} = {{A\left( {{f{\log(f)}} - f} \right)} - {\left( {{A\log f_{1}} - T_{start}} \right)f}}} & {{Equation}2}\end{matrix}$In equation 1,

$a = \frac{\ln\left( \frac{f_{1}}{f_{2}} \right)}{T}$and in equation 2,

$= {\frac{T}{\ln\frac{f_{2}}{f_{1}}}.f_{1}}$is the start frequency of the exponentially swept chirp pulse and f₂ isthe stop frequency of the exponentially swept chirp pulse. T is thepulse duration of the exponentially swept chip pulse and T_(start) isthe pulse start time.

Exponentially swept chirp signals have the characteristic that the groupdelay between fundamental and harmonic responses to the chirp signals isa function of the N^(th) order harmonic. More specifically, the groupdelay between the fundamental and harmonic responses to the chirpsignals is not a function of the frequency of the harmonic responses,e.g. the instantaneous frequency of the chirp signals corresponding tothe harmonic responses. Accordingly, the fundamental and the N^(th)order harmonic responses for an exponentially swept chirp signal sum toform their own respective impulse responses offset by the difference incorresponding group delays between the corresponding harmonic responsesand the corresponding fundamental response, what is otherwise referredto as the time delay between the corresponding harmonic responses andfundamental response.

These response characteristics of exponentially swept chirp signals arefurther illustrated by the following equations. Equation 3 is theinstantaneous frequency of the exponentially swept chirp signal.

$\begin{matrix}{{f_{instant}(t)} = {\frac{1}{2\pi}\frac{\partial{\theta_{time}(t)}}{\partial t}}} & {{Equation}3}\end{matrix}$Equation 4 is the production time for the fundamental responseτ_(groupDelay)(f) of the exponentially swept chirp signal.

$\begin{matrix}{{\tau_{groupDelay}(f)} = {{- \frac{1}{2\pi}}\frac{\partial{\theta_{freq}(f)}}{\partial f}}} & {{Equation}4}\end{matrix}$As follows, the production time for the fundamental responseτ_(groupDelay)(f), as shown in Equation 5, can be represented as afunction of the start frequency f₁ and the stop frequency f₂ of theexponentially swept chirp pulse.

$\begin{matrix}{{\tau_{groupDelay}(f)} = {T\frac{\ln\left( \frac{f}{f_{1}} \right)}{\ln\left( \frac{f_{2}}{f_{1}} \right)}}} & {{Equation}5}\end{matrix}$Further, the production time for the N^(th) order harmonic {right arrowover (τ)}_(groupDelay)(f) of the exponentially swept chirp signal can berepresented as shown in Equation 6.

$\begin{matrix}{{{\hat{\tau}}_{groupDelay}(f)} = {T\frac{\ln\left( \frac{f}{{Nf}_{1}} \right)}{\ln\left( \frac{f_{2}}{f_{1}} \right)}}} & {{Equation}6}\end{matrix}$Accordingly, the time delay Δ_(t) between the corresponding N^(th) orderharmonic responses and the fundamental response for the exponentiallyswept chirp signal can be expressed by Equation 7.

$\begin{matrix}{\Delta_{t} = {{{\tau_{groupDelay}(f)} - {{\hat{\tau}}_{groupDelay}(f)}} = {T\frac{\ln(N)}{\ln\left( \frac{f_{2}}{f_{1}} \right)}}}} & {{Equation}7}\end{matrix}$

As shown in Equation 7, Δ_(t) is a function of N but not a function ofƒ, e.g. the instantaneous frequency of the chirp signal corresponding tothe harmonic responses. Therefore, across frequency, all N^(th) orderharmonics have the same group delay and will thus sum to form a“harmonic” impulse response. Specifically, all frequencies arising froma particular harmonic order can arrive at the same time, creating aharmonic impulse response that is offset from a correspondingfundamental impulse response by the time delay Δ_(t).

As the harmonic responses for an N^(th) order harmonic can be summed toeffectively form a single harmonic impulse response, an exponentiallyswept ultrasound chirp pulse can effectively create two impulseresponses, a fundamental response and a corresponding N^(th) harmonicresponse. Specifically, backscatter from a subject region created inresponse to an exponentially swept ultrasound chirp pulse interactingwith the subject region can include a fundamental response and one ormore harmonic responses, e.g. corresponding to each N harmonic. Theseresponses, as shown in Equation 7, are displaced in time by the timedelay Δ_(t). This time delay can be a known amount, e.g. based on N andthe start and stop frequencies f₁ and f₂ of the exponentially sweptultrasound chirp pulse.

This time delay between the harmonic response(s) and the fundamentalresponse to the exponentially swept chirp can be dependent on thepresence of non-linearity in the subject region. Specifically, this timedelay between the fundamental response and the harmonic response(s) canbe created when the subject region interacting with the exponentiallyswept chirp includes non-linearity. Conversely, when the subject regionlacks non-linearity, then the created fundamental response and theharmonic response(s) can lack this time shift. In turn, the time delaycreated in response to non-linearity in the subject region can serve asa basis for identifying non-linear properties of the subject region.Specifically, the time delay between the fundamental response and theharmonic response(s) can form the basis for the superposition of two ormore images created from the ultrasound backscatter. In turn, the amountof displacement present between the two or more superposition images,e.g. based at least in part on the time delay between the fundamentalresponse and the harmonic response(s), can be analyzed to identifynon-linear properties of the subject region.

FIG. 2 shows the time offset between fundamental and harmonic responsesthat is created when the subject region has non-linearity. Specifically,FIG. 2 is a plot 200 of intensities of fundamental and harmonicresponses to an exponentially swept ultrasound chirp pulse as a functionof time for both linear and non-linear subject regions. As shown in FIG.2 , both the linear subject region and the non-linear subject regionhave a fundamental impulse response at time 0.0 uS, 202. Additionally,and as shown in FIG. 2 , the non-linear subject region has a timeshifted harmonic response 204 at time −2.0 uS, 206. However, the linearsubject region does not show corresponding time shifted harmonicresponse(s), e.g. due to the lack of non-linearity of the linear subjectregion.

FIG. 3A is a positive phase image 300 of a subject region createdthrough a Gaussian ultrasound transmit profile. FIG. 3B is a negativephase image 302 of the subject region created through the Gaussianultrasound transmit profile. FIG. 3C is a sum image 304 of the imagesshown in FIGS. 3A and 3B. FIG. 3D is a difference image 306 of theimages shown in FIGS. 3A and 3B.

The Gaussian ultrasound transmit profile is typically used in formingimages through ultrasound. Specifically, phase inversion or a positiveoriented pulse and a negative oriented pulse through a Gaussianultrasound transmit profile used to generate two separate images throughharmonic mode imaging. In turn, the fundamental component can cancel outwhen the two images are combined to leave only the harmoniccomponent(s). The corresponding positive phase image 300 shown in FIG.3A is created through a positive narrowband Gaussian transmit profilewhile the corresponding negative phase image 302 is created through anegative narrowband Gaussian transmit profile.

As shown in the positive and negative phase images 300 and 302, pointsin the imaging field are offset by 10 mm. For example, the positivephase image 300 has a point 308 at 60 mm that is offset from adjacentpoints, e.g. the point at 50 mm, by around 10 mm. The same can be seenin the negative phase image 302, where points, e.g. the point at 60 mm310, are offset from adjacent points by around 10 mm. Further and asshown in the positive and negative phase images 300 and 302, thepositive phase and negative phase images 300 and 302, the harmonicsignal(s) are not offset from the fundamental signal(s). Specifically,corresponding harmonic signal(s) and fundamental signal(s) form singlecorresponding points, e.g. point 308, and not two separate points, aswill be shown in greater detail later. This shows the lack ofseparation, e.g. due to time delay, that is created through applicationof a typical ultrasound transmit profile, e.g. a Gaussian ultrasoundtransmit profile.

This lack of separation between corresponding harmonic signal(s) andfundamental signal(s) is further illustrated in the sum image 304 andthe difference image 306 shown in FIGS. 3C and 3D. The sum image 304 ofthe positive oriented pulse and the negative oriented pulse applied tocreate the corresponding positive and negative phase images 300 and 302represents the fundamental signal(s). Further, the difference image 306of the positive oriented pulse and the negative oriented pulse appliedto create the corresponding positive and negative phase images 300 and302 represents the harmonic signal(s). As shown, in the sum image 304,the fundamental signal at 60 mm is a single point 312. Similarly, in thedifference image 306, the harmonic signal is also a single point 314that is located at 60 mm. The points 312 and 314 are both at 60 mm anddo not show a separation of depth corresponding to a lack of time delaybetween the fundamental and harmonic signals.

FIG. 4A is an intensity plot of fundamental and harmonic responses to anarrowband Gaussian transmit profile centered at a 10 mm depth. FIG. 4Bis an intensity plot of the fundamental and harmonic responses to thenarrowband Gaussian transmit profile centered at a 20 mm depth. FIG. 4Cis an intensity plot of the fundamental and harmonic responses to thenarrowband Gaussian transmit profile centered at a 30 mm depth. FIG. 4Dis an intensity plot of the fundamental and harmonic responses to thenarrowband Gaussian transmit profile centered at a 40 mm depth. FIG. 4Eis an intensity plot of the fundamental and harmonic responses to thenarrowband Gaussian transmit profile centered at a 50 mm depth. FIG. 4Fis an intensity plot of the fundamental and harmonic responses to thenarrowband Gaussian transmit profile centered at a 60 mm depth.

As can be seen in FIG. 4C, the response from the fundamental signal 412and the response from the harmonic component 414 are both collocated inspace at approximately 30 mm of depth. The same collocation of thefundamental and harmonic signal can bee see from the other intensityplots FIGS. 4A, 4B, 4D, 4E, and 4F. This further shows that a narrowbandGaussian transmit profile, that is the typical transmit used inultrasound systems, does not produce an offset in distance between thefundamental and harmonic components.

FIG. 5A is a positive phase image 500 of a subject region createdthrough an exponentially swept ultrasound chirp signal. FIG. 5B is anegative phase image 502 of the subject region created through theexponentially swept ultrasound chirp signal. FIG. 5C is a sum image 504of the images shown in FIGS. 5A and 5B. FIG. 5D is a difference image506 of the images shown in FIGS. 5A and 5B.

FIGS. 5A-D show the time delay created between fundamental and harmonicresponses to an exponentially swept ultrasound chirp signal. In thepositive phase image 500, the fundamental signal is located at the point508 at 30 mm. Further, the harmonic response in the positive phase image500 is at point 510 before 30 mm, which is offset from the point 508 ofthe fundamental response at 30 mm. This offset corresponds to the timedelay between the fundamental and harmonic responses created throughapplication of the exponentially swept ultrasound chirp signal. Thisspatial offset is also shown in the negative phase image 502 where thefundamental response is located at point 512 at 30 mm, while theharmonic response is located at point 514, which is offset from thepoint 512 of the fundamental response at 512.

This time separation between corresponding harmonic signal(s) andfundamental signal(s) is further illustrated in the sum image 504 andthe difference image 506 shown in FIGS. 5C and 5D. The sum image 504 ofthe positive oriented exponentially swept ultrasound chirp pulse and thenegative oriented exponentially swept ultrasound chirp pulse,corresponding to FIGS. 5A and 5B, represents the fundamental signal(s).Further, the difference image 506 of the positive oriented exponentiallyswept ultrasound chirp pulse and the negative oriented exponentiallyswept ultrasound chirp pulse, corresponding to FIGS. 5A and 5B,represents the harmonic signal(s). As shown in FIG. 5C, there is afundamental response at point 516 at 30 mm. Further and as shown in FIG.5D, there a harmonic response at point 518. The harmonic response atpoint 518 is shifted from the fundamental response at point 516.Specifically, the fundamental response at point 516 is at 30 mm, whilethe harmonic response at point 518 is shifted closer to 26 mm. Thisspatial shift corresponds to the time shift between the fundamentalresponse and the harmonic response to the exponentially swept ultrasoundchirp pulses.

FIGS. 6A-F are intensity plots of fundamental and harmonic responses ofa subject region to an exponentially swept ultrasound chirp signalcentered at varying depths of the subject region. As shown in FIG. 6C,the fundamental response, e.g. at point 600, is not collocated at adepth of 30 mm with the harmonic response, e.g. at point 602. The samenon-collocation of the fundamental and harmonic signals can be seen fromthe other intensity plots FIGS. 6A, B, D, E, and F with respect to rangeat the points located at other increments of 10 mm offsets. As such, theexponentially swept ultrasound chirp signal is able to separate intime/distance the harmonic and fundamental responses.

FIGS. 7A-F are plots of sums and differences of the fundamental andharmonic responses shown in FIGS. 6A-F at the varying depths of thesubject region. As can be seen from the target at 30 mm the responsefrom the fundamental signal, at point 700, is located at the expectedrange, while that of the harmonic signal is located closer to the 26 mmrange, at point 702. A similar offset in time/range is also observedfrom the points throughout the entire graph. This clearly demonstratesthat not only are the harmonic and fundamental responses separated intime/distance, but also the signal response that is associated with thefundamental and that with the harmonic can also be separated foranalysis, in particular for identifying non-linear properties of thesubject region.

FIG. 8 is a flowchart 800 of an example method for identifyingnon-linear properties of a subject region through an exponentially sweptultrasound chirp pulse. The example method shown in FIG. 8 , and othermethods and techniques for ultrasound imaging described herein, can beperformed by an applicable ultrasound imaging system, such as theultrasound system 100 shown in FIG. 1 . For example, the techniques forultrasound imaging described herein can be implemented using either orboth the ultrasound transducer 110 and the main processing console 118,e.g. the image processor 112, of the ultrasound system 100.

At step 802, ultrasound information of a subject region is collected.The ultrasound information can include ultrasound information of one ormore exponentially swept ultrasound chirp purses transmitted towards asubject region. For example, the ultrasound information can include atransmit profile of one or more exponentially swept ultrasound chirppulses transmitted towards the subject region. Further, the ultrasoundinformation can include backscatter information of both fundamental andharmonic responses generated by the subject region in response to one ormore exponentially swept ultrasound chirp pulses transmitted towards thesubject region.

As the exponentially swept ultrasound chirp pulse produces time shiftedharmonic and fundamental responses, the backscatter information caninclude information related to the time shifted harmonic and fundamentalresponses. For example, the ultrasound information can include theharmonic and fundamental responses time shifted with respect to eachother as a result of non-linearity in the subject region. In turn, theharmonic and fundamental responses can be analyzed, e.g. based on thetime shift, to identify non-linear properties of the subject region.

The ultrasound information can include a plurality of ultrasound images,or otherwise data used to generate the plurality ultrasound images, ofthe subject region based on the fundamental and harmonic signals. Theplurality of ultrasound images of the subject region can be superimposedwith respect to each other based on one or more spatial offsets. Forexample, a feature in the subject region can be displaced by a spatialoffset in the plurality of ultrasound images. The one or more spatialoffsets can correspond to the fundamental and harmonic signals.Specifically, the one or more spatial offsets can correspond to one ormore time delays between the harmonic and fundamental signals. In turnand as will be discussed in greater detail later, the spatial offset(s)in the superimposed ultrasound images can serve as a basis foridentifying non-linear properties of the subject region from theultrasound information.

At step 804, one or more corresponding harmonic responses and acorresponding fundamental response can be separated from the ultrasoundinformation for each of the one or more exponentially swept ultrasoundchirp pulses. The corresponding harmonic response(s) and the fundamentalresponse can be separated from each other in the ultrasound informationto identify one or more non-linear properties of the subject region.Specifically, the corresponding harmonic response(s) and the fundamentalresponse can be separated from each other to identify a time offsetbetween the harmonic response(s) and the fundamental response. Morespecifically, the corresponding harmonic response(s) and the fundamentalresponses can be separated from each other to identify a spatial offsetbetween one or more ultrasound images generated from the harmonicresponse(s) and the fundamental response.

In turn and at step 806, one or more non-linear properties of thesubject region can be identified based on either or both thecorresponding harmonic response(s) and the fundamental response for eachof the one or more exponentially swept ultrasound chirp pulses.Specifically and as will be discussed in greater detail later, thenon-linear properties of the subject region can be identified based onthe time offset and/or the spatial offset corresponding to the harmonicresponse(s) and the fundamental response for each of the appliedexponentially swept ultrasound chirp pulses.

The fundamental response and the harmonic response(s) can be filteredfrom the ultrasound information in order to separate the harmonicresponse(s) and the fundamental response. Specifically, the fundamentalresponse and the harmonic response(s) can be separately filtered fromthe ultrasound information to separate the fundamental response and theharmonic response(s). For example, the fundamental response and theharmonic response(s) can be filtered from the ultrasound informationbased on time, e.g. to separate the fundamental response and theharmonic response(s) based on one or more time delays between thefundamental response and the harmonic response(s).

Additionally, the fundamental response and the harmonic response(s) canbe separated by canceling out the fundamental response from theultrasound information. Specifically, the ultrasound information can beprocessed to cancel out the fundamental response, effectively isolatingthe harmonic response(s) in the ultrasound information. In turn,non-linear properties of the subject region can be identified based onthe remaining harmonic response(s) and potentially in combination withthe fundamental response. The fundamental response can be canceled outfrom the ultrasound information through an applicable signal processingtechnique. For example, pulse inversion can be applied to cancel out thefundamental response from the ultrasound information.

The fundamental response and the harmonic response(s) can be correlatedwith each other from the ultrasound information to generate correlatedharmonic and fundamental response information. In turn, the non-linearproperties of the subject region can be identified from the correlatedharmonic and fundamental response information. The harmonic response(s)and the fundamental response can be correlated with each other based ontime offset(s) created between the harmonic response(s) and thefundamental response. The time offset(s), as discussed previously can becreated as a result of application of the one or more exponentiallyswept ultrasound chirp pulses to the subject region when the subjectregion includes non-linear properties. This time offset(s) can be known,based on the characteristics of the one or more exponentially sweptultrasound chirp pulses, e.g. the start and stop frequencies of thepulses. Accordingly, the non-linear properties of the subject region canbe identified based on the known time offset(s).

In identifying the non-linear properties of the subject region based onthe fundamental and harmonic response(s), one or more correspondingspatial offsets in the subject region can be identified from thecorrelated harmonic and fundamental response information. In turn, thenon-linear properties of the subject region can be identified from thespatial offsets in the subject region. The spatial offsets cancorrespond to the time delay between the fundamental and harmonicresponse(s). Further, the spatial offsets can be represented as spatialoffsets in a result of processing the ultrasound information includingthe fundamental and harmonic response(s). Specifically, the spatialoffsets can correspond to a spatial offset, e.g. of features, in aplurality of ultrasound images created based on the fundamental andharmonic response(s).

Further, in identifying the non-linear properties of the subject regionbased on the fundamental and harmonic response(s), the fundamental andharmonic response(s) can be averaged to generate averaged harmonic andfundamental response information. In turn, the non-linear properties ofthe subject region can be identified based on the averaged harmonic andfundamental response information. The fundamental and harmonicresponse(s) can be averaged through an applicable averaging techniqueapplied to the ultrasound information including the harmonic andfundamental responses. For example, coherent data averaging can beapplied to the ultrasound information to generate the averaged harmonicand fundamental response information.

The non-linear properties identified based on either or both thefundamental and harmonic response(s) for each exponentially sweptultrasound chirp signal can be identified as part of bulk non-linearproperty estimates for the subject region. For example, identifiedestimates of a non-linear property can be averaged across the subjectregion to identify a bulk non-linear property estimate for the specificnon-linear property across the subject region. Further, the non-linearproperties can be identified on a sub-region basis for differentsub-regions of the subject region. For example, values of a non-linearproperty can be identified or estimated for different portions of thesubject region. As follows, a map of non-linear properties of thesubject region can be generated. The map of non-linear properties of thesubject region can be generated based on the non-linear propertiesidentified on a sub-region basis for the subject region. For example, amap showing different values of a non-linear property across differentsub-regions of the subject region can be generated.

The subject region can be a volume region. Specifically, the subjectregion can be a volume of tissue, e.g. in-vivo tissue. For example, thesubject region can include a volume of fatty liver tissue, Cirrhoticliver tissue, Thyroid cancer tissue, Prostate cancer tissue, or Breastcancer tissue. The non-linear properties can be volume non-linearproperties of the volume region. Specifically, non-linear properties forthe volume region can be bulk non-linear property estimates for thevolume region. The ultrasound information for the volume region can begathered by an applicable ultrasound system for gathering volumeultrasound information. For example, the ultrasound information for thevolume region can be gathered by an ultrasound system that incorporatesone or more volumetric-based ultrasound transducers.

FIG. 9 is a flowchart 900 of an example method for estimating a B/Aparameter of a subject region through an exponential swept ultrasoundchirp signal. At step 902, an exponential swept ultrasound chirp signalis formed and at step 904 the signal is transmitted towards a subjectregion. At step 906, the backscatter from the transmit signal isreceived and processed into one or more images. The desired harmonicsignal, typically the second, is than correlated, at step 908, againstthe fundamental signal, e.g. based on the image(s), to determine thespatial offset in the subject region. At step 910, a B/A parameter forthe subject region is estimated based on the correlation between thefundamental and harmonic signals.

The techniques described herein can be applied in an applicableultrasound imaging mode, such as B-Mode, contrast-enhanced ultrasound(‘CEUS’), CD-Mode, 2D/3D/4D, and the like. Specifically, the techniquesdescribed herein are not limited to B-Mode but can also be applied toother modes where improved temporal resolution within a region ofinterest has substantial clinical benefits, such as CEUS.

This disclosure has been made with reference to various exemplaryembodiments including the best mode. However, those skilled in the artwill recognize that changes and modifications may be made to theexemplary embodiments without departing from the scope of the presentdisclosure. For example, various operational steps, as well ascomponents for carrying out operational steps, may be implemented inalternate ways depending upon the particular application or inconsideration of any number of cost functions associated with theoperation of the system, e.g., one or more of the steps may be deleted,modified, or combined with other steps.

While the principles of this disclosure have been shown in variousembodiments, many modifications of structure, arrangements, proportions,elements, materials, and components, which are particularly adapted fora specific environment and operating requirements, may be used withoutdeparting from the principles and scope of this disclosure. These andother changes or modifications are intended to be included within thescope of the present disclosure.

The foregoing specification has been described with reference to variousembodiments. However, one of ordinary skill in the art will appreciatethat various modifications and changes can be made without departingfrom the scope of the present disclosure. Accordingly, this disclosureis to be regarded in an illustrative rather than a restrictive sense,and all such modifications are intended to be included within the scopethereof. Likewise, benefits, other advantages, and solutions to problemshave been described above with regard to various embodiments. However,benefits, advantages, solutions to problems, and any element(s) that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, a required, or anessential feature or element. As used herein, the terms “comprises,”“comprising,” and any other variation thereof, are intended to cover anon-exclusive inclusion, such that a process, a method, an article, oran apparatus that comprises a list of elements does not include onlythose elements but may include other elements not expressly listed orinherent to such process, method, system, article, or apparatus. Also,as used herein, the terms “coupled,” “coupling,” and any other variationthereof are intended to cover a physical connection, an electricalconnection, a magnetic connection, an optical connection, acommunicative connection, a functional connection, and/or any otherconnection.

Those having skill in the art will appreciate that many changes may bemade to the details of the above-described embodiments without departingfrom the underlying principles of the invention. The scope of thepresent invention should, therefore, be determined only by the followingclaims.

What is claimed is:
 1. A method for performing diagnostic sonographycomprising: transmitting, via an ultrasound transducer, one or moreexponentially swept ultrasound chirp pulses toward a subject region;receiving, via the ultrasound transducer, backscatter of the subjectregion from the one or more exponentially swept ultrasound chirp pulses,wherein the one or more exponentially swept ultrasound chirp pulses aredefined by the equations:${{x(t)}e^{i2\pi\frac{f_{1}}{a}{({e^{at} - 1})}}},$θ(f)=A(f log(f)−f)−(A log f ₁ −T _(start))f, where${a = \frac{\ln\left( \frac{f_{1}}{f_{2}} \right)}{T}},{A = \frac{T}{\ln\frac{f_{2}}{f_{1}}}},$f₁ is a start frequency of an exponentially swept ultrasound chirppulse, f₂ is a stop frequency of the exponentially swept ultrasoundchirp pulse, T is a pulse duration of the exponentially swept ultrasoundchirp pulse, and T_(start) is a pulse start time of the exponentiallyswept ultrasound chirp pulse; collecting, using one or more processors,ultrasound information of the subject region from the backscatter;processing, using the one or more processors, the ultrasound informationto generate one or more images; separating, using the one or moreprocessors from the ultrasound information, one or more correspondingharmonic responses and a corresponding fundamental response for each ofthe one or more exponentially swept ultrasound chirp pulses;identifying, using the one or more processors, one or more non-linearproperties of the subject region based on either or both of the one ormore corresponding harmonic responses and the corresponding fundamentalresponse for each of the one or more exponentially swept ultrasoundchirp pulses; and generating, using the one or more processors, a map ofthe one or more non-linear properties of the subject region across thesubject region.
 2. The method of claim 1, wherein the subject regionincludes in-vivo tissue.
 3. The method of claim 1, wherein the one ormore non-linear properties of the subject region include one or more B/Aparameters of the subject region.
 4. The method of claim 1, furthercomprising separately filtering the corresponding fundamental responseand the one or more corresponding harmonic responses for each of the oneor more exponentially swept ultrasound chirp pulses from the backscatteras part of separating the one or more corresponding harmonic responsesand the corresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses from the ultrasoundinformation.
 5. The method of claim 1, further comprising canceling outthe corresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses from the backscatter toidentify the one or more corresponding harmonic responses for each ofthe one or more exponentially swept ultrasound chirp pulses from thebackscatter as part of separating the one or more corresponding harmonicresponses and the corresponding fundamental response for each of the oneor more exponentially swept ultrasound chirp pulses from the ultrasoundinformation.
 6. The method of claim 5, further comprising applying pulseinversion to cancel out the corresponding fundamental response for eachof the one or more exponentially swept ultrasound chirp pulses from thebackscatter.
 7. The method of claim 1, further comprising: correlatingthe one or more corresponding harmonic responses with the correspondingfundamental response for each of the one or more exponentially sweptultrasound chirp pulses to generate correlated harmonic and fundamentalresponse information; and identifying the one or more non-linearproperties of the subject region based on the correlated harmonic andfundamental response information.
 8. The method of claim 7, wherein theone or more corresponding harmonic responses are correlated with thecorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses based on a correspondingtime offset between each of the one or more corresponding harmonicresponses and the corresponding fundamental response for each of the oneor more exponentially swept ultrasound chirp pulses.
 9. The method ofclaim 7, wherein the correlated harmonic and fundamental responseinformation includes a plurality of ultrasound images of the subjectregion superimposed with respect to each other by one or morecorresponding spatial offsets, the method further comprising:determining the one or more corresponding spatial offsets from thecorrelated harmonic and fundamental response information; andidentifying the one or more non-linear properties of the subject regionbased on the one or more corresponding spatial offsets.
 10. The methodof claim 1, further comprising: applying coherent data averaging betweenthe one or more corresponding harmonic responses and the correspondingfundamental response for each of the one or more exponentially sweptultrasound chirp pulses to generate averaged harmonic and fundamentalresponse information; and identifying the one or more non-linearproperties of the subject region based on the averaged harmonic andfundamental response information.
 11. The method of claim 1, wherein theone or more non-linear properties of the subject region are identifiedas part of bulk non-linear property estimates for the subject region.12. The method of claim 1, wherein the subject region is a volumeregion, the method further comprising identifying the one or morenon-linear properties across the volume region.
 13. The method of claim12, wherein the ultrasound information is generated across the volumeregion by one or more volumetric-based ultrasound transducers.
 14. Themethod of claim 12, wherein the one or more non-linear properties of thesubject region are identified as part of bulk non-linear propertyestimates for the volume region.
 15. The method of claim 12, wherein thesubject region is a volume of tissue and the one or more non-linearproperties are properties of the volume of tissue.
 16. The method ofclaim 15, wherein the volume of tissue includes at least one of fattyliver tissue, Cirrhotic liver tissue, Thyroid cancer tissue, Prostatecancer tissue, and Breast cancer tissue.
 17. A system for performingdiagnostic sonography comprising: an ultrasound transducer configuredto: transmit one or more exponentially swept ultrasound chirp pulsestoward a subject region; receive backscatter of the subject region fromthe one or more exponentially swept ultrasound chirp pulses, wherein theone or more exponentially swept ultrasound chirp pulses are defined bythe equations: ${{x(t)}e^{i2\pi\frac{f_{1}}{a}{({e^{at} - 1})}}},$θ(f)=A(f log(f)−f)−(A log f ₁ −T _(start))f, where${a = \frac{\ln\left( \frac{f_{1}}{f_{2}} \right)}{T}},{A = \frac{T}{\ln\frac{f_{2}}{f_{1}}}},$f₁ is a start frequency of an exponentially swept ultrasound chirppulse, f₂ is a stop frequency of the exponentially swept ultrasoundchirp pulse, T is a pulse duration of the exponentially swept ultrasoundchirp pulse, and T_(start) is a pulse start time of the exponentiallyswept ultrasound chirp pulse; a main processing console configured to:collect, using one or more processors, ultrasound information of thesubject region from the backscatter; process, using the one or moreprocessors, the ultrasound information to generate one or more images;separate, using the one or more processors from the ultrasoundinformation, one or more corresponding harmonic responses and acorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses; identify, using the one ormore processors, one or more non-linear properties of the subject regionbased on either or both of the one or more corresponding harmonicresponses and the corresponding fundamental response for each of the oneor more exponentially swept ultrasound chirp pulses; and generate, usingthe one or more processors, a map of the one or more non-linearproperties of the subject region across the subject region.
 18. A systemfor performing diagnostic sonography comprising: one or more processors;and a non-transitory computer-readable medium providing instructionsaccessible to the one or more processors to cause the one or moreprocessors to perform operations comprising: transmitting, via anultrasound transducer, one or more exponentially swept ultrasound chirppulses toward a subject region; receiving, via the ultrasoundtransducer, backscatter of the subject region from the one or moreexponentially swept ultrasound chirp pulses, wherein the one or moreexponentially swept ultrasound chirp pulses are defined by theequations: ${{x(t)} = e^{i2\pi\frac{f_{1}}{a}{({e^{at} - 1})}}},$θ(f)=A(f log(f)−f)−(A log f ₁ −T _(start))f, where${a = \frac{\ln\left( \frac{f_{1}}{f_{2}} \right)}{T}},$${A = \frac{T}{\ln\frac{f_{2}}{f_{1}}}},$ f₁ is a start frequency of anexponentially swept ultrasound chirp pulse, f₂ is a stop frequency ofthe exponentially swept ultrasound chirp pulse, T is a pulse duration ofthe exponentially swept ultrasound chirp pulse, and T_(start) is a pulsestart time of the exponentially swept ultrasound chirp pulse;collecting, using one or more processors, ultrasound information of thesubject region from the backscatter; processing, using the one or moreprocessors, the ultrasound information to generate one or more images;separating, using the one or more processors from the ultrasoundinformation, one or more corresponding harmonic responses and acorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses; identifying, using the oneor more processors, one or more non-linear properties of the subjectregion based on either or both of the one or more corresponding harmonicresponses and the corresponding fundamental response for each of the oneor more exponentially swept ultrasound chirp pulses; and generating,using the one or more processors, a map of the one or more non-linearproperties of the subject region across the subject region.
 19. Themethod of claim 1, wherein identifying the one or more non-linearproperties of the subject region comprises: measuring a time delaybetween the one or more corresponding harmonic responses and thecorresponding fundamental response for each of the one or moreexponentially swept ultrasound chirp pulses; and comparing the measuredtime delay with a calculated time delay to identify the one or morenon-linear properties of the subject region.
 20. The method of claim 19,wherein the calculated time delay determined according to the followingequation:$\Delta_{t} = {T\frac{\ln(N)}{\ln\left( \frac{f_{2}}{f_{1}} \right)}}$where N represents an order of the harmonic response.
 21. The method ofclaim 20, wherein the subject region lacks a non-linearity if themeasure time delay and calculated time delay are identical.
 22. Themethod of claim 1, wherein generating a map of the one or morenon-linear properties of the subject region across the subject regioncomprises generating a map showing different values of a non-linearproperty across different sub-regions of the subject region.